TY  - JOUR
PY  - 2017//
TI  - Estimation of driver's longitudinal intention for the preceding car using EEG
JO  - Transactions of Society of Automotive Engineers of Japan
A1  - Ikenishi, Toshihito
A1  - Kamada, Takayoshi
SP  - 1127
EP  - 1134
VL  - 48
IS  - 5
N2  - The interaction between human and vehicle has been researched to reduce the traffic accident in Japan. In the research of driver assistance system, more driver friendly assistance system has been researched using the information of driver and vehicle. This system requires to achieve a better relationship between human and vehicle. In addition, it is important to find a method to determine a driver's operational intention. Therefore, we have focused on the brain activities in the biological information. The time frequency analysis such as FFT has been major method in the traditional decomposition of the electroencephalogram (EEG). However, these conventional methods can only use two-dimensional data. In our previous research, we investigated that the driver's EEG at the preceding car avoidance maneuver was decomposed by parallel factor analysis (PARAFAC), and we investigated the feature factor of longitudinal behavior for recognize and judgment from that decomposition result. PARAFAC analysis has known as a multi-channel EEG analysis of multi-dimensional data. In the previous research, we investigated the driver's EEG of during longitudinal operation using PARAFAC. Consequently, all subjects have two common factors of the frequency component which exist in the 5-10 Hz and 8-13 Hz region. Those factors were changed by the driver's mental state during visual recognition and judgment. In this paper, we estimated the driver's intention from a driver's EEG using source current distribution estimation with Hierarchical Bayesian method and the sparse logistic regression. From the estimation results, the estimation accuracy of driver's intention was higher than about 70 % of two subjects' in the longitudinal operation.<p />  <p>Language: ja</p>
LA  - ja
SN  - 0287-8321
UR  - http://dx.doi.org/10.11351/jsaeronbun.48.1127
ID  - ref1
ER  -